Abstract A proper reservoir characterization is important to decipher the effects of heterogeneity on reservoir performance due to primary, secondary, and/or enhanced oil recovery operations. As permeability is the most important flow property, an accurate reservoir characterization requires accurate permeability description as a function of space. To develop permeability descriptions, many studies have proposed methods utilizing core, log, and well testing data. These methods are often based on geostatistics and require considerable computing power for their effective implementation. In this paper, a simple and accurate method has been developed for an integrated analysis of core and log data to obtain permeability vs. depth estimates at all logged, but not necessarily cored, wells in a field. The proposed method is based on the Kozeny equation and well-known logging relationships for formation factor and water saturation estimations. This method analyses all available core and log data for a particular field to develop relationships that can be used to generate permeability vs. depth estimates at all logged wells. The method can be implemented using a spreadsheet software package. The proposed method has been successfully tested using core and log data for the Steepbank tar sand. The proposed method accurately described permeability variations for all permeability ranges between 10 md and 30 Darcy for the Steepbank tar sand. The simplicity and accuracy of the proposed method should encourage even small- to medium-sized oil companies without sophisticated computer facilities and expertise to implement some assessment of the impact of reservoir heterogeneity on process performance. Introduction Permeability estimation in uncored wells is an important step toward a preparation of the reservoir characterization needed to study the reservoir responses to primary, secondary, and/or enhanced oil recovery operations. Most often, a straight line relationship on a cross-plot of the logarithm of core-permeability vs. core-porosity for a given facies (or rock type or depositional environment) is used to estimate permeability from a log-derived porosity in uncored wells. However, many times, a significant scatter is observed on a log (k) vs. Φcross-plot, suggesting the dependence of permeability on porosity and other factors. Other factors affecting permeability may be pore size distribution, tortuosity, interconnection among pores, shaliness, presence of clay and cementing materials, grain size and shape, and presence of fractures and solution vugs, etc. The relationship between permeability and the preceding set of factors is complex. A visualization of a simple mathematical relationship between permeability and factors affecting permeability is impossible. But factors affecting permeability may also affect the responses from various logs. Therefore, several investigators(l-9) have discussed their empirical efforts to relate permeability to log (or log-derived) responses. An abbreviated discussion of various empirical relationships proposed in the literature appears in Appendix A. A summary of various permeability estimation techniques also appears in Reference (10). Recently, Amaefule et al.(l1) have proposed a method, based on the Kozeny(l2) equation, to identify hydraulic flow units using detailed core analysis data. Their method can be simplified to devise an integrated core-log interpretation method for permeability estimation in uncored wells.